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. 2008 Dec;40(4):447-58.
doi: 10.1080/02791072.2008.10400651.

Applying classification and regression tree analysis to identify prisoners with high HIV risk behaviors

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Applying classification and regression tree analysis to identify prisoners with high HIV risk behaviors

Linda Frisman et al. J Psychoactive Drugs. 2008 Dec.

Abstract

Among prisoners, past research has associated several factors with HIV risk behaviors, including illicit drug use, engaging in sex trade, older age (for drug-related risk), younger age (for sex-related risk), low education, low income, type of offense, history of abuse, mental health disorders, vulnerability and low self-perceived efficacy. This study employs data collected through the Transitional Case Management study of the Criminal Justice Drug Abuse Treatment Studies collaborative to analyze characteristics of prisoners who engaged in high-risk behaviors prior to incarceration. For the first 787 participants of this study, we employed recursive partitioning techniques to better identify groups at varying levels of HIV risk behaviors. Those more likely to engage in risky needle use were White and either unemployed and less likely to justify their behavior, or employed with poor decision making capacity. Risky sexual behavior was associated with a general tendency toward risk-taking or a history of unstable housing. Those engaging in any type of HIV risk behavior were risk-takers in general and were aged 25 to 47 with a history of unstable housing. Recursive partitioning, a technique seldom used previously, offers a useful method for identifying subpopulations at elevated risk for HIV risk behaviors.

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Figures

Figure 1
Figure 1
Classification tree for risky needle behaviors among participants
Figure 2
Figure 2
Classification tree for risky sexual behaviors among participants
Figure 3
Figure 3
Classification tree for risky HIV/AIDS behaviors among participants
Figure 4
Figure 4
Likelihood of Engaging in HIV Risk Behaviors

References

    1. Alarid LF, Marquart JW. HIV/AIDS knowledge and risk perception of adult women in an urban area jail. Journal of Correctional Health Care. 1999;6 (1):97–127.
    1. Altice FL, Marinovich A, Khoshnood K, Blankenship KM, Springer SA, Selwyn PA. Correlates of HIV infection among incarcerated women: Implications for improving detection of HIV infection. Journal of Urban Health: Bulletin of the New York Academy of Medicine. 2005;82 (2):312–326. - PMC - PubMed
    1. Altice FL, Mostashari F, Selwyn PA, Checko PJ, Singh R, Tanguay S, Blanchette EA. Predictors of HIV infection among newly sentenced male prisoners. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology. 1998;18:444–453. - PubMed
    1. Belenko S, Lin J, O’Connor L, Sung H, Lynch KG. Sexual and physical victimization as predictors of HIV risk among felony drug offenders. AIDS and Behavior. 2005;9 (3):311–323. - PubMed
    1. Biggs D, DeVille B, Suen E. A method of choosing multiway partitions for classification and decision trees. Journal of Applied Statistics. 1991;18 (1):49–62.

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